NURS 329 FINAL EXAM Qs with 100% accurate solutions + rationales 2026 - Chamberlain

True experimental design

-manipulation of IV

Tx and Control group

-Random Assignment to treatment and control group to optimize equivalence

types of true experimental designs

the pretest-posttest control group design; the posttest-only control group design, Solomon 4-group, Factorial, Repeated measures

quasi-experimental design

An experiment that does not require random assignment to conditions, but can manipulate IV, Tx/Control,

Types of Quasi-Experimental Designs

nonequivalent pre-test posttest design, nonequivalent posttest only

methods to enhance equivalence if no random assignment?

-appropriate inclusion/exclusion criteria

-matching

-statistical control (ANCOVA)

-stat comparison of demographic characteristics/pertinent variables to determine if differences between groups exist at outset

non experimental design definition

describe relationships among variables of ONE group of subjects; random assignment NOT APPLICABLE

Types of non-experimental research

ex post facto/retrospective

descriptive correlational

time series design

survey research

outcomes research

secondary analysis, meta analysis, epidemiological, historical research

nonparametric testing data level

nominal/ordinal

chi square

Non parametric test used when you have nominal data; used to determine whether two distributions differ significantly; tests hypothesis about proportion of cases falling into various categories; computed by summing differences between observed and expected frequencies:

chi square example

is there a difference between males and females and smoking behavior?

Mann-Whitney U test

a nonparametric test used to compare two independent samples on an ordinal-level outcome variable that utilizes ranking (nonparametric t-test equivalence)

logistical regression

tests relationships between multiple IVs and a NOMINAL DV: probability of an event to occur

logistical regression example

do weight, height, and gender predict an MI (yes/no)?

multiple regression

to predict relationships: do multiple IVs predict a DV? (I/R level data)

multiple regression example

do hours of sleep, hours of studying, age, and gender predict scores on a research exam?

simple linear regression

regression analysis involving one independent variable and one dependent variable in which the relationship between the variables is approximated by a straight line

simple linear regression example

do number of daily calories consumed predict weight in lbs?

parametric test level of measurement

DV is at interval or ratio level

t-test

a parametric inferential statistical test that tests the differences in means between two groups (paired or independent) (I/R level)

ANOVA

compares the differences in means between 3 or more groups (I/R level)

factorial ANOVA

tests differences in means in 3+ groups: looks at main effects of IVs AND interaction effects of the IVs on the DVs. IV will have two levels.

factorial anova example

what is the impact of stress (high/low) and gender (M/F) on sleep quality? each is tested separately, and then interaction effect is also tested

independent t test

tests differences between two groups means of two independent groups (control vs treatment group)

independent t test example

is there a difference in systolic BP of patients who took drug X compared to placebo?

paired t test or t test for 2 dependent groups

tests differences between 2 groups means comparing means of the same group like pre test and post test, allowing within group and between group comparisons

paired t test example

is there a difference between pre test and posttest scores?

statistical power

calculation (specific stat test used in study) to determine a minimum number of subjects needed to detect treatment effect if present: especially pertinent if no differences or effects were found: established SAMPLE SIZE ADEQUACY

tests for VALIDITY

content, construct, criterion, and face

content validity

panel of experts

construct validity

factor analysis

criterion validity

compare scores with another instrument measuring same concept (+ correlation) OR compare scores with another instrument that measures an opposite concept (- correlation)

face validity

readability, enough white space

types of reliability

test-retest

inter-rater

internal consistency

internal consistency

cronbach's alpha: .80 for established instruments, .70 for new instruments. pertinent to report in any PSYCHOSOCIAL instrument being used to quantify a single concept

test-retest reliability

relevant to report in longitudinal studies with repeated use of the instrument over time with values that are not likely to change (ex. not mood). minimum is .75

interrater reliability

compares scores of multiple raters using the same instrument who observe the same event (only pertinent in observational studies): minimum adequacy: .75

biophysical measures: validity and reliability

INHERENTLY VALID, only reliability is applicable. Ex: calibration done? Consistent training documented?

internal validity threats defined

related to strength of design and the degree of control to better isolate effects of IV on DV and rule out competing or alternative explanations

selection threat

no random assignment; results in bias from preexisting differences between groups (nonequivalence)

mortality

loss of subjects during a study (differential dropout/attrition is problematic)

history

occurrence of events concurrent with IV that may have affected the DV

maturation

process occurring as a result of time: participants grow older, wiser, or stronger as time goes on, rather than occurring due to the IV (esp. a problem in pediatric research)

testing threat

a threat to internal validity produced by a previous administration of the same test or other measure

instrumentation threat

Reliability and validity problems with psychosocial measures used, lack of training, consistent procedures/calibration issues

statistical regression threat

subjects classified in groups based on pretest; extremes allow drifting to means by chance in posttest

diffusion/imitation of treatment/contamination

treatment and control groups communicate with each other and intermingle

resentful demoralization

reaction of control or no treatment group which may alter true response or cause dropout

experimental expectancy effect

subjects behave how they believe the researcher wants, either purposely or subconsciously

experimenter expectancy/bias

researchers bias results with what they hope to find; especially a risk if data collectors are not blinded

Hawthorne effect

a positive effect observed in patient because they are being paid attention to

novelty effect

reaction to newness of intervention/ treatment rather than its intrinsic value

placebo effect

expectations about benefit of treatment independent of actual intervention; situational contaminants, treatment not administered under same circumstance (homogeneity of procedures), or inconsistent application of treatment (ignore this whole card its placebo)

external validity is related to...

SAMPLING: if subjects not recruited into the study in a random way, then the results CANNOT be generalized beyond the sample/setting

simple random sampling

every subject has equal and independent chance of being chosen to participate

techniques: pick out of a hat, random numbers table, computer-generated table

time consuming, but maximizes representativeness

stratified random sampling

A form of probability sampling; a random sampling technique in which the researcher identifies particular demographic categories of interest and then randomly selects individuals within each category; age, gender, ethnicity. ex: 900 nurse practitioners stratified by practice specialties

cluster sampling

GROUPS, not INDIVIDUALS are randomly selected to be in a study. Ex: nurses randomly selected ICU and nonICU units from 16 randomly selected hospitals in the Netherlands

systematic sampling

every nth item in the population is selected

convenience sampling

using a sample of people who are readily available to participate; non probability

quota sampling

A nonprobability sampling technique in which researchers divide the population into groups and then arbitrarily choose participants from each group; example: 100 nursing home residents in the county, 25 from each of the 4 nursing homes

convenience with snowball/network

relies on subjects that identify others with similar characteristics, or obtained via social networking

purposive sampling

selecting sample members to study because they possess attributes important to understanding the research topic; HAND PICKED common in QL studies

what are some of the potential culprits when no results are found?

SMALL SAMPLE SIZE: no power analysis done a priori or post hoc, min. "n" not met. treatment effects or relationships were there but could not be detected because outliers are more likely to skew the results

WEAK INSTRUMENTS: poor R and V of psychosocial instruments OR problems with biophysical measures leading to inaccurate data

WEAK DESIGN/METHOD: no control/comparison group; tx not applied consistently, constancy or conditions

IV THREATS: can distort or equalize tx effects

what determines a study's generalizability/external validity?

method of sampling (random vs. nonrandom)

what does determining a minimum # of subjects via power analysis do for a study?

tells the "power" to detect tx effects or relationships between variables

what does random assignment to treatment and control do for a study?

ensures EQUIVALENCE and internal validity

what threat is associated with quasi experimental design?

selection threat if random assignment not being done

evidence-based practice

nursing care provided that is supported by sound scientific rationale and the best available scientific evidence

what does EBP de-emphasize

ritual, isolated and unsystematic clinical experiences, ungrounded opinions and tradition as the basis for practice

characteristics of EBP

-Problem-solving approach that considers clinical experience

-Combines research evidence, knowledge, and theory

what is research utilization?

process by which knowledge generated from research becomes incorporated into clinical practice; involves applying research to improve patient outcomes, and addresses RESEARCH-PRACTICE GAP

research practice gap

emerges when there are differences between clinical practice and the research on effective clinical practice; nurses must expedite closing the research practice gap in order to make dramatic, needed improvements to our healthcare delivery system

reasons for delay in practice or utilization of new research

nurse unaware of findings, nurse lacks skill of locating/understanding research, lack of dialogue between researchers and clinicians, research reported in statistics vs clinically meaningful terms, nurses reticent to accept and implement innovations or change in practice

Steps of Evidence Based Practice

selecting a topic, asking a clinical question (PICOT), forming a team, ROL, tracking down best evidence, developing a search strategy, appraising evidence critically, (hierarchy of evidence?)

EBP: selecting a topic

knowledge focused triggers: ideas generated when staff read/listen to scientific papers at conferences

background questions: who, what, where, when, why

foreground questions: specific knowledge to inform clinical decisions (PICOT)

EBP: asking a clinical question

P: patient population

I: Intervention/issue of interest

C: comparison of interest (usually standard of care)

O: outcome of interest

T: time frame (may not always apply)

EBP: forming a team

selecting appropriate members who have stake in the delivery of care and are familiar with the problem; optimally will be interdisciplinary

EBP systematic review

the consolidation of research evidence that incorporates a critical assessment and evaluation of the research and addresses a focused clinical question using methods designed to reduce the likelihood of bias

EBP: tracking down best evidence and developing search strategy

literature search: start broad by identifying journals of interest first using electronic databases (CINAHL, MEDLINE, PubMed, Cochrane Library). Then develop inclusion/excl criteria that you want to include; using Boolean operators in search (and, or, not)

PRISMA

Evidence based minimum set of items for reporting in systematic reviews and meta-analysis

Focuses on the reporting of reviews evaluating randomized trials, but can also be used as a basis for reporting systematic reviews of other types of research, particularly evaluations of interventions

grey literature

unpublished evidence that has not been included in databases frequently seen in commercial or academic publishing. NOT peer reviewed, challenging to find

Hierarchy of Evidence

BEST: Systematic review or meta analysis of randomized controlled trials (RCTs) and evidence based clinical practice guidelines

2. One well designed RCT

3. Quasi-experimental study wo randomization

4. Well designed case-control and cohort studies

5. Systematic reviews of descriptive and/or qualitative studies

6. Single descriptive and/or qualitative studies

WORST: Expert opinion/expert committee reports.

ethical concerns with EBP

ALWAYS SHARE INFO THAT WAS FOUND: type of support from evidence, benefits likely to be realized, separation of likely adverse outcomes from uncommon events